DOCK on AWS
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DOCK on AWS
First time set up
- 1. create an account
define these roles
AmazonEC2SpotFleetRole, AWSServiceRoleForEC2Spot and AWSServiceRoleForEC2SpotFleet.
- 2. create awsuser (optional!)
- 3. create an S3 bucket "results2021"
within create dockfiles, database.txt output1
- 4. set up aws cli access
set up the ability to upload. On your client computer you need awscli. you need to set up your credentials. you need to upload. also work on download.
- 5. AWS Batch. choose new batch experience.
set up compute environments. env1. managed. env1. enable computer environment. AWSBatchService role. Spot. maximum on demand price 100. minimum vCPUs 0. max vCPUs 256. desired vCPUs 0. BEST_FIT_PROGRESSIVE. set up job queue. queue1. set up job definition. jobdef4. EC2. retry 1. execution timeout 14400. image btingle/dockaws:latest . bash . vcpus 1. memory 2048. S3_DOCKFILES_LOCATION s3://results2021/dockfiles SHRTCACHE /tmp AWS_ACCESS_KEY_ID xxxxx S3_INPUT_LOCATION s3://btingletestbucket/input AWS_SECRET_ACCESS_KEY xxxxx S3_OUTPUT_LOCATION s3://btingletestbucket/output1 AWS_DEFAULT_REGION us-east-2 Enable privileged mode root. log driver awslogs
Set up database list to run
- 1. make sure zinc-22/sets is current (current within 7 days? ask JJI if in doubt)
- 2. decide on the range you want to dock. here we choose lead-like
- 3. decide on the platform you want to dock on. here we choose AWS (S3)
cd zinc-22/sets cat *.lead-like.*.s3 > ~/.aws/my-todock-list.s3
- 4. get your dockfiles. Use JK-coloring. Coloring and Subcluster Matching
- 5. upload dockfiles and database selection to AWS S3.
(you already set up ~/.aws/credentials previously)
aws s3 cp myjob-dockfiles.tgz s3://results2021/dockfiles/ aws s3 cp my-todock-list.s3 s3://results2021/databases/
Recommend uploading a test set to make sure things work.
grep xaa my-todock-list.s3 > my-to-dock-sample.s3 grep -v xaa my-todock-list.s3 > my-to-dock-balance.s3 aws s3 cp my-to-dock*.s3 s3://results2021/databases/
- 6. go to aws.amazon.com and go to S3 to confirm your files landed correctly.
- 7. to go Batch and review Compute Environments, Job Queues, Job Definitions and refine if needed.
- 8. go to Jobs and set up a new job using your sample.
You are testing that you can do a round-trip with your data before you launch at scale.
- 9. verify test job ran correctly. Also check time, nmatch, sampling, and look for errors in the logs indicating problems.
- 10. launch at scale.
- 11. montior job progress
- 12. when done, process the results.
- 1. Upload someproject.dockfiles.tgz into dockfiles.
- 2. reference database set up above.
- 2. set up output directory in S3.
- 3. set up job
- 4. run job
after job completes
- 1. check for complete and run
- 2. combine blazing fast
- 3. extract mol2 files
- 4. download data for processing and review.
- 1. move to glacier
- 2. run a variation of the job
- 3. harvest a variation of the job
- troubleshooting: https://aws.amazon.com/premiumsupport/knowledge-center/batch-invalid-compute-environment
- watching out for spending too much money
- more debugging https://aws.amazon.com/premiumsupport/knowledge-center/batch-job-stuck-runnable-status/